1. Field of the Invention
The present invention relates to an electronic camera, and more particularly, to a method for processing digital data output from an image sensor of a single sensor color electronic camera, using a plurality of directional coefficients.
2. Description of the Related Art
An image sensor for converting an input scene into an electronic signal senses the intensity of light which changes with respect to each divided region on the sensor, that is, the regular pattern of pixels. A color filter array (CFA) is installed on the sensor, and each pixel of the sensor senses the intensities of color signals which pass through the CFA.
In converting a color signal into an electronic signal, it is preferable that image data sensed in three color planes, which sense red, green, and blue, respectively, is all captured at the same time. This is because image data sensed in the three color planes must be appropriately mixed to obtain a high quality color picture.
If only one plane capable of sensing the three colors is used instead of the three color planes, the plane is referred to as a single sensor. In general, a single sensor CFA has the structure of a normal pattern of a color filter so that each pixel senses one color. A single sensor Charge Coupled Device (CCD) or a CMOS image sensor is a device for sensing a scene which is input to a camera, and outputs digital data having information on the intensity of a color which is sensed by each pixel. A video data item output from the single sensor CCD or CMOS image sensor has information on only one color signal out of Red (R), Green (G), and Blue (B). Therefore, a data item of the single sensor image sensor should generate information on the remaining two colors by using an interpolation method.
A data structure in which a color information data item does not have information on all three colors for expressing one pixel, but has information on any one color of the three colors, is referred to as a Bayer array structure.
FIG. 1 is a diagram of a Bayer array. In the Bayer array of FIG. 1, a variety of interpolation methods may be used in order to obtain R, G, and B colors of each pixel, and the interpolation performance changes greatly depending on which interpolation method is selected.
First, an interpolation method using a first order filtering method will now be explained.
When a linear interpolation method is used, the G component of pixel (1,1) having information on the B component is expressed as the following equation:
      G    11    =                    G        01            +              G        10            +              G        12            +              G        21              4  
In the linear interpolation method, the picture quality of a complex part of the image, for example, a region having a spatial edge, is deteriorated. An example of a spatial edge is a coin on a sheet of white paper. In this case, there is a spatial edge with no continuity of signal at the boundary between the paper and the coin.
To solve the problem, a method in which an edge component is divided into a horizontal direction component and a vertical direction component and then interpolation is applied to the direction having a smaller degree of edge slope, was proposed. For example, when the G component of pixel (1,1) of FIG. 1 is to be obtained, if the degree of horizontal direction edge slope is less than the degree of vertical direction edge slope, then
            G      11        =                            G          10                +                  G          12                    2        ,and if the degree of vertical direction edge slope is less than the degree of horizontal edge slope, then
      G    11    =                              G          01                +                  G          21                    2        .  
However, in the method, the picture quality of a part having a diagonal edge component is deteriorated.
To solve the problems of the above-described two methods, a method for using second order Laplacian filtering was proposed.
In the Laplacian filtering method, assuming that the difference between color signals in a local region of an image is constant (Gi−Ri=const1, Gi−Bi=const2, and Bi−Ri=const3, where i denotes the position of a pixel), a new interpolation method is applied. For example, if the edge component of the horizontal direction is less, the G component of pixel (2,2) of FIG. 1 is
      G    22    =                              G          21                +                  G          23                    2        +                                        2            ⁢                          R              22                                -                      R            20                    -                      R            24                          4            .      
For a normal image, the method provides advantages of simplicity in hardware structure and high performance. However, in diagonal edges of some cases where the assumption is not true, for example, in a synthetic image, the method cannot solve the deterioration of picture quality as other existing methods.